



import argparse

from tax import checkpoints

from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM







def  lowerCAmelCase_	(lowerCAmelCase__:		Tuple		,						lowerCAmelCase__:		List[str]		,						lowerCAmelCase__:		Optional[Any]  ):





			"""simple docstring"""


			UpperCAmelCase_:		Any							      =     AutoConfig.from_pretrained(lowerCAmelCase__  )
			UpperCAmelCase_:		Dict							      =     FlaxAutoModelForSeqaSeqLM.from_config(config=lowerCAmelCase__  )
			UpperCAmelCase_:		Optional[Any]							      =     checkpoints.load_tax_checkpoint(lowerCAmelCase__  )

			UpperCAmelCase_:		Any							      =     """wi_0""" in tax_model["""target"""]["""encoder"""]["""layers_0"""]["""mlp"""]

			if config.model_type == "t5":
						UpperCAmelCase_:		List[str]							      =     """SelfAttention"""
			if config.model_type == "longt5" and config.encoder_attention_type == "local":
						UpperCAmelCase_:		Optional[Any]							      =     """LocalSelfAttention"""
			elif config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
						UpperCAmelCase_:		Optional[int]							      =     """TransientGlobalSelfAttention"""
			else:
						raise ValueError(
						    """Given config is expected to have `model_type='t5'`, or `model_type='longt5` with `encoder_attention_type`"""
						    """ attribute with a value from ['local', 'transient-global]."""  )

			# Encoder
			for layer_index in range(config.num_layers  ):
						UpperCAmelCase_:		str							      =     F'layers_{str(lowerCAmelCase__  )}'

						# Self-Attention
						UpperCAmelCase_:		Union[str, Any]							      =     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""key"""]["""kernel"""]
						UpperCAmelCase_:		List[str]							      =     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""out"""]["""kernel"""]
						UpperCAmelCase_:		int							      =     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""query"""]["""kernel"""]
						UpperCAmelCase_:		str							      =     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""value"""]["""kernel"""]

						# Global input layer norm
						if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
									UpperCAmelCase_:		int							      =     tax_model["""target"""]["""encoder"""][layer_name]["""attention"""]["""T5LayerNorm_0"""]["""scale"""]

						# Layer Normalization
						UpperCAmelCase_:		Dict							      =     tax_model["""target"""]["""encoder"""][layer_name]["""pre_attention_layer_norm"""]["""scale"""]

						if split_mlp_wi:
									UpperCAmelCase_:		Optional[int]							      =     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
									UpperCAmelCase_:		int							      =     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
						else:
									UpperCAmelCase_:		List[str]							      =     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

						UpperCAmelCase_:		str							      =     tax_model["""target"""]["""encoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

						# Layer Normalization
						UpperCAmelCase_:		int							      =     tax_model["""target"""]["""encoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

						# Assigning
						UpperCAmelCase_:		Union[str, Any]							      =     flax_model.params["""encoder"""]["""block"""][str(lowerCAmelCase__  )]["""layer"""]
						UpperCAmelCase_:		str							      =     tax_attention_key
						UpperCAmelCase_:		Any							      =     tax_attention_out
						UpperCAmelCase_:		List[str]							      =     tax_attention_query
						UpperCAmelCase_:		Any							      =     tax_attention_value

						UpperCAmelCase_:		List[str]							      =     tax_attention_layer_norm

						# Global input layer norm
						if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
									UpperCAmelCase_:		List[Any]							      =     tax_global_layer_norm

						if split_mlp_wi:
									UpperCAmelCase_:		int							      =     tax_mlp_wi_a
									UpperCAmelCase_:		Union[str, Any]							      =     tax_mlp_wi_a
						else:
									UpperCAmelCase_:		Tuple							      =     tax_mlp_wi

						UpperCAmelCase_:		Union[str, Any]							      =     tax_mlp_wo
						UpperCAmelCase_:		Optional[Any]							      =     tax_mlp_layer_norm

						UpperCAmelCase_:		Tuple							      =     flax_model_encoder_layer_block

			# Only for layer 0:
			UpperCAmelCase_:		str							      =     tax_model["""target"""]["""encoder"""]["""relpos_bias"""]["""rel_embedding"""].T
			UpperCAmelCase_:		List[Any]							      =     tax_encoder_rel_embedding

			# Side/global relative position_bias + layer norm
			if config.model_type == "longt5" and config.encoder_attention_type == "transient-global":
						UpperCAmelCase_:		Union[str, Any]							      =     tax_model["""target"""]["""encoder"""]["""side_relpos_bias"""]["""rel_embedding"""].T
						UpperCAmelCase_:		Dict							      =     tax_encoder_global_rel_embedding

			# Assigning
			UpperCAmelCase_:		Union[str, Any]							      =     tax_model["""target"""]["""encoder"""]["""encoder_norm"""]["""scale"""]
			UpperCAmelCase_:		Union[str, Any]							      =     tax_encoder_norm

			# Decoder
			for layer_index in range(config.num_layers  ):
						UpperCAmelCase_:		Union[str, Any]							      =     F'layers_{str(lowerCAmelCase__  )}'

						# Self-Attention
						UpperCAmelCase_:		Any							      =     tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""key"""]["""kernel"""]
						UpperCAmelCase_:		Optional[Any]							      =     tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""out"""]["""kernel"""]
						UpperCAmelCase_:		int							      =     tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""query"""]["""kernel"""]
						UpperCAmelCase_:		int							      =     tax_model["""target"""]["""decoder"""][layer_name]["""self_attention"""]["""value"""]["""kernel"""]

						# Layer Normalization
						UpperCAmelCase_:		Tuple							      =     tax_model["""target"""]["""decoder"""][layer_name]["""pre_self_attention_layer_norm"""][
						    """scale"""
						]

						# Encoder-Decoder-Attention
						UpperCAmelCase_:		Any							      =     tax_model["""target"""]["""decoder"""][layer_name]["""encoder_decoder_attention"""]
						UpperCAmelCase_:		Union[str, Any]							      =     tax_enc_dec_attention_module["""key"""]["""kernel"""]
						UpperCAmelCase_:		Tuple							      =     tax_enc_dec_attention_module["""out"""]["""kernel"""]
						UpperCAmelCase_:		str							      =     tax_enc_dec_attention_module["""query"""]["""kernel"""]
						UpperCAmelCase_:		Any							      =     tax_enc_dec_attention_module["""value"""]["""kernel"""]

						# Layer Normalization
						UpperCAmelCase_:		Optional[Any]							      =     tax_model["""target"""]["""decoder"""][layer_name]["""pre_cross_attention_layer_norm"""]["""scale"""]

						# MLP
						if split_mlp_wi:
									UpperCAmelCase_:		List[Any]							      =     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_0"""]["""kernel"""]
									UpperCAmelCase_:		str							      =     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi_1"""]["""kernel"""]
						else:
									UpperCAmelCase_:		Any							      =     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wi"""]["""kernel"""]

						UpperCAmelCase_:		List[str]							      =     tax_model["""target"""]["""decoder"""][layer_name]["""mlp"""]["""wo"""]["""kernel"""]

						# Layer Normalization
						UpperCAmelCase_:		Optional[Any]							      =     tax_model["""target"""]["""decoder"""][layer_name]["""pre_mlp_layer_norm"""]["""scale"""]

						# Assigning
						UpperCAmelCase_:		Any							      =     flax_model.params["""decoder"""]["""block"""][str(lowerCAmelCase__  )]["""layer"""]
						UpperCAmelCase_:		Union[str, Any]							      =     tax_attention_key
						UpperCAmelCase_:		List[Any]							      =     tax_attention_out
						UpperCAmelCase_:		Optional[int]							      =     tax_attention_query
						UpperCAmelCase_:		List[Any]							      =     tax_attention_value

						UpperCAmelCase_:		Dict							      =     tax_pre_attention_layer_norm

						UpperCAmelCase_:		List[Any]							      =     tax_enc_dec_attention_key
						UpperCAmelCase_:		Tuple							      =     tax_enc_dec_attention_out
						UpperCAmelCase_:		Optional[Any]							      =     tax_enc_dec_attention_query
						UpperCAmelCase_:		Any							      =     tax_enc_dec_attention_value

						UpperCAmelCase_:		Any							      =     tax_cross_layer_norm

						if split_mlp_wi:
									UpperCAmelCase_:		List[Any]							      =     tax_mlp_wi_a
									UpperCAmelCase_:		Optional[int]							      =     tax_mlp_wi_a
						else:
									UpperCAmelCase_:		Dict							      =     tax_mlp_wi

						UpperCAmelCase_:		Dict							      =     tax_mlp_wo

						UpperCAmelCase_:		int							      =     txa_mlp_layer_norm

						UpperCAmelCase_:		Tuple							      =     flax_model_decoder_layer_block

			# Decoder Normalization
			UpperCAmelCase_:		List[Any]							      =     tax_model["""target"""]["""decoder"""]["""decoder_norm"""]["""scale"""]
			UpperCAmelCase_:		Tuple							      =     txa_decoder_norm

			# Only for layer 0:
			UpperCAmelCase_:		str							      =     tax_model["""target"""]["""decoder"""]["""relpos_bias"""]["""rel_embedding"""].T
			UpperCAmelCase_:		Optional[Any]							      =     tax_decoder_rel_embedding

			# Token Embeddings
			UpperCAmelCase_:		Optional[int]							      =     tax_model["""target"""]["""token_embedder"""]["""embedding"""]
			UpperCAmelCase_:		Optional[Any]							      =     txa_token_embeddings

			# LM Head (only in v1.1 and LongT5 checkpoints)
			if "logits_dense" in tax_model["target"]["decoder"]:
						UpperCAmelCase_:		Dict							      =     tax_model["""target"""]["""decoder"""]["""logits_dense"""]["""kernel"""]

			flax_model.save_pretrained(lowerCAmelCase__  )
			print("""T5X Model was sucessfully converted!"""  )


if __name__ == "__main__":
	a      :  int			     =			argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    '--t5x_checkpoint_path', default=None, type=str, required=True, help='Path the T5X checkpoint.'
	)
	parser.add_argument('--config_name', default=None, type=str, required=True, help='Config name of LongT5/T5 model.')
	parser.add_argument(
	    '--flax_dump_folder_path', default=None, type=str, required=True, help='Path to the output FLAX model.'
	)
	a      :  Optional[int]			     =			parser.parse_args()
	convert_tax_checkpoint_to_flax(args.tax_checkpoint_path, args.config_name, args.flax_dump_folder_path)











def  lowerCAmelCase_	(lowerCAmelCase__:		int  ):





			"""simple docstring"""


			if num <= 0:
						raise ValueError("""Input must be a positive integer"""  )

			UpperCAmelCase_:		Tuple							      =     [True] * (num + 1)

			UpperCAmelCase_:		Tuple							      =     2
			while p * p <= num:
						if primes[p]:
									for i in range(p * p		,						num + 1		,						lowerCAmelCase__  ):
												UpperCAmelCase_:		Optional[Any]							      =     False
						p += 1

			return [prime for prime in range(2		,						num + 1  ) if primes[prime]]


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	a      :  Optional[Any]			     =			int(input('Enter a positive integer: ').strip())
	print(prime_sieve_eratosthenes(user_num))






